I decided to treat workmind as a docs-first execution system for Cloudflare DevRel Q1 2026, not an application codebase: the core outcome is a structured planning workspace where strategy, execution, and operating memory stay aligned and queryable.

What We Built

• A planning repository centered on Markdown operating docs, with clear lanes for strategy (docs/strategy/), execution (docs/execution/), industry inputs (docs/industry-insights/), people planning, and operations/tooling.
• A practical onboarding path captured in README.md: start with devrel-strategy.md, then devrel-2026-planning.md, then DEVREL-ACTION-ITEMS.md.
• A lightweight retrieval workflow via QMD (qmd.yml) plus a canonical index in content/catalog.md to keep planning context discoverable.
• One concrete automation surface (scripts/sync_meeting_transcripts.py) to pull meeting transcripts into local Markdown so discussion history can feed planning artifacts.

Why We Built It

• I optimized for execution clarity over platform complexity: the repository purpose and agent guidance both point to planning fidelity, date accuracy, and maintaining actionable docs rather than building new services.
• The directory structure reflects how DevRel work is actually run: long-horizon strategy, quarter actions, launch one-pagers, staffing, and operational routing in separate but connected areas.
• The transcript + indexing setup indicates a deliberate decision to turn ongoing conversations into durable memory instead of losing context in chat threads.
• With no recent commit/session signals yet, this initial baseline matters: it defines the operating model before iteration starts, so future updates can be measured against an explicit starting point.

How It Works

• Planning flows top-down: mission and annual assumptions in docs/strategy/ inform Q1 actions in docs/execution/, including product one-pagers.
• New external signals are summarized into docs/industry-insights/ and linked into the content index, so strategy updates are evidence-backed.
• Meeting output is synced into Markdown through scripts/sync_meeting_transcripts.py, then folded into planning docs instead of living in separate tooling silos.
• Agent behavior is constrained by AGENTS.md: preserve factual accuracy, keep writing concise and actionable, and update indexes/cross-links when new documents are added.